No 177
The Effect of Perceived
Regional Accents on
Individual Economic
Behavior:
A Lab Experiment on
Linguistic Performance,
Cognitive Ratings and
Economic Decisions
Stephan Heblich,
Alfred Lameli,
Gerhard Riener
February 2015
IMPRINT DICE DISCUSSION PAPER Published by düsseldorf university press (dup) on behalf of Heinrich‐Heine‐Universität Düsseldorf, Faculty of Economics, Düsseldorf Institute for Competition Economics (DICE), Universitätsstraße 1, 40225 Düsseldorf, Germany www.dice.hhu.de Editor: Prof. Dr. Hans‐Theo Normann Düsseldorf Institute for Competition Economics (DICE) Phone: +49(0) 211‐81‐15125, e‐mail: [email protected] DICE DISCUSSION PAPER All rights reserved. Düsseldorf, Germany, 2015 ISSN 2190‐9938 (online) – ISBN 978‐3‐86304‐176‐2 The working papers published in the Series constitute work in progress circulated to stimulate discussion and critical comments. Views expressed represent exclusively the authors’ own opinions and do not necessarily reflect those of the editor. 1
The Effect of Perceived Regional Accents on Individual Economic
Behavior: A Lab Experiment on Linguistic Performance, Cognitive Ratings
and Economic Decisions
February 2015
Stephan Heblich1, Alfred Lameli2, Gerhard Riener*3
Affiliations
1
University of Bristol, CESifo, IZA and SERC, Address: Department of Economics, 8
Woodland Road, Bristol BS8 1TN (UK)
2
Research Centre Deutscher Sprachatlas and ADW Mainz, Address: Hermann-Jacobsohn-
Weg 3, 35032 Marburg (Germany)
*3
Düsseldorf Institute for Competition Economics, University of Mannheim , CRC PEG
University of Göttingen and Department of Economics, University of Mannheim, Address: L7
3-5, 68131 Mannheim (Germany), Phone: +49-621-181-1894, Email: [email protected].
2
Abstract
Does it matter if you speak with a regional accent? Speaking immediately reveals something
of one’s own social and cultural identity, be it consciously or unconsciously. Perceiving
accents involves not only reconstructing such imprints but also augmenting them with
particular attitudes and stereotypes. Even though we know much about attitudes and
stereotypes that are transmitted by, e.g. skin color, names or physical attractiveness, we do not
yet have satisfactory answers how accent perception affects human behavior. How do people
act in economically relevant contexts when they are confronted with regional accents? This
paper reports a laboratory experiment where we address this question. Participants in our
experiment conduct cognitive tests where they can choose to either cooperate or compete with
a randomly matched male opponent identified only via his rendering of a standardized text in
either a regional accent or standard accent. We find a strong connection between the linguistic
performance and the cognitive rating of the opponent. When matched with an opponent who
speaks the accent of the participant’s home region – the in-group opponent –, individuals tend
to cooperate significantly more often. By contrast, they are more likely to compete when
matched with an accent speaker from outside their home region, the out-group opponent. Our
findings demonstrate, firstly, that the perception of an out-group accent leads not only to
social discrimination but also influences economic decisions. Secondly, they suggest that this
economic behavior is not necessarily attributable to the perception of a regional accent per se,
but rather to the social rating of linguistic distance and the in-group/out-group perception it
evokes.
Introduction
Language as the primary means of human communication forms a large part of social
practice. It is shaped by speakers' idiosyncratic experiences [1] and by long-lasting cultural
traits [2]. In everyday communication, both of these components, the individual and the
cultural, evoke stereotypes and social ratings. Spoken language is thus a signal that elicits
particular conceptualizations about the speaker [3]. The extent to which these determine nonlinguistic behavior is still poorly understood.
The identifying potential of language has recently attracted researchers from different fields,
including linguists [4,5], psychologists [6,7] and economists [8,9]. Measuring the effect of
language on social behavior and individual interaction is however very difficult, given its
dependence on specific contexts and individual preconditions. The most common way of
3
addressing this challenge is to focus on individual attitudes and judgments. It turns out that
listening to non-native or regional accents can invoke judgments about the credibility of
speakers [7,10], their character traits and cognitive capacities [6,11], or even influence the
perception of facts in criminal cases [12,13]. There is also evidence that the use of an accent
can imply strategic advantages, e.g., in sales conversations [9] or job interviews [14], where
accents suggest a joint identity. What remains open is to what extent attitudes really suit the
action. While extensive research has already established a link between attitudes and action
for individual characteristics like beauty or ethnicity [15–17], there has been widespread
disregard for the gap between reported attitudes to accents and actual behavior. This is
unfortunate, because accents are qualitatively different from other distinguishing factors (e.g.,
physical attractiveness) and effectively constitute a unique parameter of human interactions
[18] that can be used strategically.
This paper addresses the gap between accent perception and individual action. Our first
hypothesis is that accent perception does affect individual behavior. Since accents distinguish
social groups, the effect should differ when perceiving in-group or out-group accents [19]..
This is our second hypothesis. Finally, we take up the finding that out-group accents can
invoke discriminatory judgments and pose our third hypothesis that in-group favoritism is
manifested by a feeling of cognitive superiority.
To formally test these hypotheses, we combine techniques from experimental economics and
linguistics to develop a picture of differentiated behavioral discrimination. To omit potential
influences from cross-country differences we focus on regional accents within one country—
in our case Germany—that indicate a higher similarity between speakers and listeners than
foreign accents [14]. Regional accents typically originate in local dialects [20]. With the
introduction of national radio and television programs later, dialects began to converge to the
codified written language [21]. This process leaves us with regional accents as an
intermediate stage between dialects and standard language today (note that other studies—
especially in the German tradition—may use the terms ‘regiolect’, ‘regional dialect’, ‘regional
standard’ or ‘spoken standard’ to refer to this intermediate stage). In Germany, regional
accents typically consist of phonological and inflectional features that are still understandable
for individuals from other regions. They are commonly used in everyday communication and
subject to noticeable variation depending on contextual requirements [22,23]. Importantly,
regional accents still reflect historic variation in norms, habits, and conventions that emerged
over generations within dialect regions [24,25]. Already in childhood, regional accents turn
out to be a more relevant dimension of social preferences than foreign accents or race [26,27].
4
This is why regional accents today still distinguish social groups that differ in acceptance,
popularity and loyalty [28]. In the following, we explore this distinguishing feature of
regional accents to assess how differences in accents affect individual interactions.
The main challenge for our research design is to account for the possibility that using an
accent may either be strategic or correlated with context-specific and/or individual
characteristics. Both cases would induce spurious correlations [29]. To overcome potential
problems of confounding influences and identify an unbiased effect, our experiment meets the
following three criteria. First, the controlled laboratory environment rules out any biases from
unobserved context effects causing individuals to use regional accent strategically. This
involves fixed interactions as well as fixed language treatments. Second, our experimental
strategy separates accent effects from possibly confounding speaker characteristics like voice
or intonation. Third, we present a strategy to distinguish general social discrimination of
accent speakers from specific social discrimination of out-group accent speakers.
Our experimental setup confronts experimental participants (EP) with three types of randomly
assigned language samples, one in German standard language (in the following standard
accent) and two in regional accents. All language samples are provided by native language
informants (LI). The first regional accent is chosen to match the Eastern Middle German
accent spoken in the EPs home region, Thuringia. The second accent originates in a different
region, namely Bavaria. Both accents rank among the most prominent accents in German
census data [30]. Our setup implies that EPs perceive Eastern Middle German as in-group
accent and Bavarian as out-group accent. The experiment consists of cognitive tests where
EPs have to compare their own performance with the LI’s expected performance. If they
expect to outperform the LI they can choose to compete. If successful, they will receive a
higher remuneration but will lose money if their performance is equal or worse than the LI. If
EPs do not rate their own performance higher than the LI’s performance, they can choose to
cooperate instead, or choose a strategy that is independent of the LI’s performance. The only
thing EPs know about their opponents is their (randomly matched) accent. Any systematic
difference in the choice to cooperate or compete when being matched with an in-group or outgroup LI thus reveals how accent perception affects action.
Our results confirm our first hypothesis, that accent perception affects individual interactions.
Moreover, we find evidence for a systematically different treatment of the out-group accent.
EPs are less willing to cooperate with the out-group accent LI and choose to compete instead.
Since the spoken accent is not related to the LI’s performance by design, we follow [31] and
consider this differential treatment as expression of social discrimination. To the extent that
5
individuals can choose to use a standard accent or a regional accent, our results also allow for
the reverse argument that individuals can influence the economic behavior of interaction
partners through the choice to employ regional accents or standard accent.
In the remainder, we will explain our experimental setup in detail, present and discuss their
relevance and implications.
Material and Methods
Experimental strategy
As outlined in Fig. 1 (upper part), our strategy proceeds in two stages. In the first stage,
language informants (LI) with competence in standard accent and regional accent generate
two language samples, one in standard accent and one in regional accent. Additionally, they
perform a set of five cognitive tasks which are remunerated according to performance (piece
rate).
Fig. 1. Experimental strategy and subsequent empirical analysis. The standard accent sample (Stand) is shown
in white, the Bavarian accent (Bav) in gray, and the Thuringian accent (Thur) in black. The first stage of the
experiment shows the two language informants (LI) who provide two language samples each. In the second
stage, we relate economically relevant choices to the assigned treatments and match one of four language
samples randomly with experimental participants (EP). In the analysis, we first estimate within-speaker
differences to eliminate the effect of individual confounding characteristics (First Differences) and then calculate
the difference in those first differences (Second Difference) to account for stochastic discrimination against
regional accent. Contrasting the expected choices leaves us with an unbiased discrimination effect δ (cf.
following explanations).
In the second stage, we invite experimental participants (EP) to the laboratory where they
perform the same set of cognitive tasks plus one extra task at the beginning. This first
cognitive task involves one of the randomly assigned language samples generated in the first
stage. EPs’ remuneration depends on their performance in these tasks as well. However, after
the first task, EPs can also choose remuneration schemes that incorporate their expectation of
the LI’s performance. If they believe that they are better than the LI they can compete,
6
otherwise cooperate or ignore the LI. By linking the EPs’ choice to compete or cooperate to
the randomly assigned language sample, we can assess how accent perception influences
individual behavior.
First Stage
Language Informants (LI). All LIs were recruited at Marburg University. We invited
candidates to a linguistic assessment, consisting of three tests. First, we tested the LI’s general
competence in speaking standard accent without any regional marking. Secondly, we tested
the LI’s competence in speaking with the regional accent of their home region using a
competence test introduced by [32]. Thirdly, we tested their reading competence with both
standard accent without regional marking and regional accent. To assess their performance,
we use a dialectality measure developed by [33]. Based on the three tests, we chose one LI
from Bavaria (originating from Ingolstadt) and one LI from Thuringia (originating from
Erfurt). Both LIs were socialized in regional accent and standard accent and speak it
interchangeably. Both were 23 year old male undergraduate students.
Language Samples. We generated four language samples that represent our language
treatments. Each LI provided two language samples, one in standard German and one in either
the in-group accent (Thuringian) or the out-group accent (Bavarian). Employing the same LI
for a language sample in a regional accent and one in a standard accent provides a constant
voice quality that allows us to account for confounding individual characteristics like tone
pitch, speech rate or intonation. At the same time this enables us to control social
characteristics such as age or sex [34]. Similarly, we focused on male speakers to avoid
gender effects. Finally, we acoustically normalized the speech signals so that our language
samples were played back at the same volume, eliminating noise from breathing or throat
clearing, and standardizing the time signals (pauses).
The language samples comprised of an 81 word accident report and a list of words. The
accident report was designed to include language features that characterize both dialects. For
the Thuringian sample this included, e.g., the centralization of back vowels [u:] and [o:] or the
weakening of unvoiced consonants [p] and [t] of voiced consonants [b] and [d]. For the
Bavarian sample this included replacing rounded front vowels [y:] and [ø:] by unrounded [i:]
and [e:] or using the apical instead of the uvular /r/. The standard accent sample has no such
regional phenomena. All samples lasted approximately 30 seconds.
7
Fig. 2. Regional intensity across the language samples. The figure shows the regional intensity of our language
samples relative to codified standard German (d = 0). We find a strong and comparable deviation of both
regional language samples from codified standard. At the same time, we find an insignificant difference between
these two regional accent samples and between the two standard accent samples.
Fig. 2 shows the results of a formal linguistic test [33,35] comparing the regional intensity of
our language samples. The intensity d is calculated as the number of micro-phonetic features
(e.g. voicing, manner, or location of articulation) that deviate from codified standard German
divided by the overall number of words in the text. A value of d = 0 would suggest perfect
compliance with codified standard German. A value of d = 1 means that, on average, one
phonetic feature per word differs from codified standard German. Very pronounced local
accents may have a score of d > 2 or even d > 3 [33,22]. [36] finds that an intensity of d > 2
leads to intelligibility problems. Reassuringly, we do not measure an intensity larger than
d = 2 in our language samples. We further find that neither the two interregional accent
samples (Bavarian vs. Thuringian: T = -1.079, p = .284) nor the standard accent samples
(Bavarian vs. Thuringian: T = -1.354, p = .180) show a statistically significant difference
while the individual speakers’ samples in the regional accent and the standard accent are
significantly different; (regional accent vs. standard accent: Bavarian: T = 6.801, p < .001;
Thuringian: T = 8.545, p < .001). The latter nicely illustrates the dual competence of our LIs.
At the same time it is reassuring that our design rules out biases from differing accent
intensities.
Second Stage
Experimental Participants (EP). The second stage of the experiment was conducted at the
computer laboratory at the University of Jena in September 2010 and September 2011. EPs
were recruited via the ORSEE online recruitment system [37]. Two selection criteria were
involved in the choice of EPs: (i) we excluded economics and linguistics students and (ii) we
8
excluded persons who had already performed similar tasks in a related experiment. Overall,
we conducted 19 laboratory sessions with 18 EPs per session, leaving us with a total of 342
observations.
Our research design required that we focus on EPs who originated from the same dialect
region. Unfortunately, ORSEE does not include information about the participants’ home
region. Instead, we had to select the relevant observations after the experiment, based on a
questionnaire, following two criteria. Firstly, we chose EPs from the federal states of
Thuringia and Saxony, which comprise the Eastern Middle German dialect group. Secondly,
we only selected EPs who had grown up in this dialect region and whose parents also came
from there. This latter criterion ensures that the EPs share a comparable social background.
After dropping all EPs that did not meet these criteria, we ended up with a subset of 167 EPs
who were primarily undergraduate students at the University of Jena.
Within each session we randomly matched the four language samples provided by the LIs in
the first stage with the EPs. This procedure avoids confounding treatment effects with session
effects. Moreover, EPs were not aware of the other treatments, so as to reduce experimenter
demand effects (cf. [38]). We obtained the following observation numbers for each pairing of
EP and LI: standard accent spoken by the Thuringian LI: N = 41; standard accent spoken by
the Bavarian LI: N = 40; Thuringian accent: N = 36; Bavarian accent: N = 50.
Tasks. The experiment consisted of eight sets of tasks (cf. Table 1), all of them programmed
in zTree [39]. Tasks 1–5 were designed as cognitive tests that have been shown to be good
predictors of general economic success (cf. SI 1 for examples of these tasks). They cover a
wide range of cognitive abilities including (a) language competence (tasks 1, 4), (b) the ability
to abstract (task 2), (c) logic (task 3), and (d) memory (task 5);skills that have been shown to
be important determinants for success in the labor market [40]. To control for individual
preferences that may affect the choice of a payment scheme we further included standard
games that test tournament and risk aversion (tasks 6‒7). A final task presented a
questionnaire that helps us collected personal and linguistic information about the EPs (task
8).
Task 1 – Listening Comprehension: The regional treatments were introduced in a listening
comprehension task at the beginning of the experiment. In this task, EPs listened individually
on headphones to a text read out by a randomly matched LI who spoke either standard
German, or with a Bavarian or Thuringian accent. This 81-word accident report took a format
familiar from radio news bulletins. After listening to the text, EPs were asked to answer
9
multiple choice questions about it. This setting was designed as a typical listening
comprehension task as encountered in school or university language courses. The text we
used is part of the German language examination (Deutsche Sprachprüfung für den
Hochschulzugang; DSH) required for university entrance in Germany. In all setups, EPs had
to remember a number of facts from the text. In this context, the use of regional accents
presented an additional test complication.
Task 2 – Mathematics: The mathematics task required EPs to add up five two-digit numbers.
Calculators were not allowed but paper and pencil were provided by the experimenter. All
numbers were randomly drawn and presented in the following way: An open-ended series of
calculations was to be performed within a set time of five minutes. As soon as EPs had
completed one task they received a new one. A count of correctly solved calculations was
always visible on the screen. After receiving the instructions, EPs could familiarize
themselves with the task in a two-minute non-paid trial round. This task was included on the
basis of [41] studies of male and female attitudes towards competition.
Task 3 – Logic: In this task, EPs were asked to answer questions from the 2002 GRE
(Graduate Record Examination) logic section. GRE is a standardized test used as a
recruitment tool for doctoral candidates in Europe and the US. Each question described a
particular situation on which the EPs had to answer several combinational logic-based
questions.
Task 4 – Language: In the language task, EPs were asked to place five words in order into a
grammatically correct sentence (declarative sentence). Each word was assigned a unique
number and EPs had to order these numbers to specify the correct sentence structure.
Whenever they completed one sentence correctly, a new one was presented until five minutes
had passed. This task had previously been used to analyze gender task stereotypes [42].
Task 5 – Memory: As in the listening comprehension task EPs listened to a list of 16 words
read out by the LI in a treatment-specific variety (i.e., either in standard accent or regional
accent). The EPs were asked to memorize as many words as possible. Subsequently, they
were presented with a list of words on the screen and the EPs had to identify the words that
had previously been read out.
Task 6 – Tournament Aversion: To test for tournament aversion, we used the results from the
word order task (which is according to [42] only mildly gender-biased) and asked EPs
whether they wanted to receive € 1 or to have their result compared with a randomly chosen
result from another individual in the room. If their result was better, they would receive € 3, if
not, they would forfeit payment.
10
Task 7 – Risk Aversion: To control for risk aversion, we applied a simplified procedure based
on [43] that had previously been used by [44]. EPs were presented with a list of five pairs of
different lotteries. In each case, EPs had the choice between a safe lottery X that guaranteed
payment of € 0.50 and a risky lottery Y in which they had an equal chance of winning
amounts ranging from € 0.90 to € 1.50 or zero. In general, we would expect more risk adverse
individuals to be slower to switch from lottery X to lottery Y. One pair of lotteries was
randomly selected and the decision was paid out.
Task 8 – Questionnaire: At the end, EPs were asked to fill out a questionnaire. This included
biographic information and four sets of linguistic questions that helped us determine the EPs’
attitudes toward dialects and their region of origin.
Payment Schemes. In stage one of our experiment, LIs had been asked to perform the same
four tasks that the EPs were asked to do in the laboratory. LIs earned a piece rate of one ECU
(Experimental Currency Unit) per correct answer. The exchange rate between ECU and Euro
is 1 EUR = 1.7 ECU. This exchange rate is calculated from a pilot study and provides that
students earn on average the hourly wage rate of a research assistant at the University of Jena.
In stage two, EPs received € 0.50 per correct answer in Task 1 as an incentive to listen
carefully. After that, EPs were informed that they would subsequently perform four other
tasks that their matched LI had completed earlier for a fixed remuneration per correctly solved
task. Tasks 2‒5 were remunerated according to one of the following payment schemes (cf.
also Fig. 3).
1. Piece rate: EPs were paid € 0.50 for each correctly solved piece independent of
other subjects’ performance.
2. Tournament: The EP’s score in a specific task is compared to the matched LI‘s
score. If the EP’s score was higher than the LI‘s score; she earned €1.40 per piece.
If they were equal to or lower; they received € 0.20 per piece.
3. Revenue sharing: EPs’ earnings were based on the average score of the EP and the
LI, and paid at a piece rate of € 0.50.
11
Fig. 3. Payoff matrix for tasks 2–5. Color indicates potential gains (green) and losses (orange) compared to piece
rate. Piece rate: m = Ʃca * € 0.50; revenue sharing: m = (Ʃca + Ʃcb) / 2 * € 0.50; tournament: m = Ʃca * € 1.40 if
Ʃca > Ʃcb otherwise m = Ʃca * € 0.20, with m = payoff; ca = successful completion of task by participant A;
cb = successful completion of task by speaker B.
EPs chose a payment scheme for tasks 2‒5 before performing a task. In task 5 (memory task);
they were not informed that the list was to be read out by the matched LI. The remuneration
schemes suggest that EPs would choose tournament if they thought they were better than the
LI and revenue sharing if they were afraid to score less. Piece rate is the outside option in case
EPs do not want to compare themselves to anybody. Since the language sample was the LI’s
only known characteristic, any systematic difference in the EPs choice to cooperate or
compete was caused by their accent perception. Specifically, the EPs’ choice helps us uncover
whether out-group LIs are more often found in a competitive situation. We would interpret a
significantly lower willingness to cooperate as an indication of social discrimination because
speaking with a regional accent is independent of the LI’s performance in the tasks.
The average experimental session lasted approximately 75 minutes and EPs earned an average
payoff of € 10.13. This payoff is roughly equivalent to the hourly wage of a research assistant
at German universities. The maximum (minimum) payoff amounted to € 31.10 (€ 3.40,
respectively).
Empirical Strategy
We analyzed the experimental outcome in a difference-in-differences framework (cf. Fig. 1;
lower part). The first differences compare the choices of EPs who are matched with the same
LI speaking regional accents (Bav/Thur) or standard accent (Stand). Differentiating between
the expected choice of those EPs who were listening to the LI speaking Thuringian (Bavarian)
accent and those who were listening to the same informant speaking with the standard accent
reveals EP’s judgment of regional accents relative to standard accent. Since we are comparing
the same LI in two contexts (regional accents and standard accent) this measure is
independent of all fixed characteristics of the LI (like tone pitch or intonation) that may
systematically affect the EPs’ choice.
12
These first differences are then compared with each other to measure the discrimination
against the out-group regional accent relative to the in-group regional accent. The second
difference (δ) thus measures whether EPs choose tournament significantly more often when
being matched with the out-group LI. In this way, we can distinguish between general social
discrimination of accent speakers and a specific social discrimination of the out-group accent
speaker.
Empirically, this setup corresponds to a simple dummy variable interaction model with two
main effects for language (regional accent or standard accent) and origin (Thuringia and
Bavarian) and an interaction term that marks observations matched with a Bavarian accent. To
calculate this difference-in-differences, we employ the following model to estimate EPs’
choice in the four different tasks:
schemei = a + b1 Bavariani + b 2 Accenti + b3 Bavariani ´ Accenti + X i¢y + òi
where scheme is a categorical outcome variable describing the payment scheme chosen by EP
indexed i. Bavarian is an indicator variable taking the value 1 if the LI is from Bavaria and 0
if he is from Thuringia. Similarly, Accent is an indicator variable taking the value 1 if the
language sample is regional accent (Thuringian or Bavarian) and 0 if it is standard accent.
Bavarian ´ Accent is the interaction between the two indicator variables Bavarian and
Accent. Although the inclusion of control variables is not necessary as the treatments are
orthogonal to any other influencing variable, the controls may improve the precision of the
estimates obtained and help us to identify the sources of observed discrimination patterns.
Accordingly, Xi stands for a matrix of individual-level control variables that might influence
the choice of the payment scheme including session fixed effects, age, gender, self-assessed
performance, and the results from task 6 and task 7 indicating tournament aversion and risk
aversion. Finally, ɛ is an i.i.d. error term.
The two parameters of interest are β2 and β3.
β2 gives us the probability of choosing
competition when the Thuringian LI speaks with a regional accent and β3 gives us the change
in probability of choosing competition when the Bavarian LI speaks with a regional accent.
Results
Table 2 summarizes the experimental design in the second stage. While there are no major
differences in the scheme choice between the Thuringian and the Bavarian LI in the standard
accent condition, there is a large increase of over 12 percentage points between the rates of
choice of tournament when the Bavarian rather than the Thuringian accent is perceived from
13
the same LI (Table 2).
Comparing the distributions of scheme choices for standard accent or regional accent spoken
by the Bavarian LI or the Thuringian LI, there is a significant difference only in the regional
treatments. This is confirmed by a multinomial logit model. EPs do not choose the tournament
more often when perceiving the Thuringian accent, but there is a significant increase in
tournament take up when matched with the Bavarian accent over all tasks (Pearson’s χ² < .05).
Fig. 4 summarizes the predicted margins of tournament take-up, showing a significant impact
of Bavarian accent on tournament.
Fig. 4. Predicted margins of Bavarian accent conditional on age and gender controls with the 90% confidence
interval. Standard errors are clustered by subject. This graph shows the predicted margins of the probability of
choosing tournament from a multinomial logit model (Table 3) using age and gender as additional control
variables. EPs do not chose the tournament more often when perceiving the Thuringian accent, but tournament
take up increases strongly when perceiving the Bavarian accent.
When the outcome categories of revenue sharing and piece rate are pooled, in the aggregate
(Fig. 5; A) EPs choose tournament more often when they perceive the Bavarian accent
(robustness is also given when estimating a mixed model, cf. Table S1). This result is largely
driven by two tasks (Fig. 5; B): the logic task (rr Tourn/Bav = 3.88, p < .05), which is particularly
aimed at problem solving skills, and the language task (rr Tourn/Bav = 4.84, p < .01), which targets
linguistic performance. At the same time, there is some indication that EPs avoid the
tournament option when listening to the Thuringian accent in these tasks. In the math task
(ability to abstract) and the memory task (ability to store and recall information) we do not
find such behavior. One explanation for the effect heterogeneity is that EPs presume that the
performance in the language and logic tasks depends on linguistic abilities. Our results then
14
show that EPs expect the out-group accent speaker to perform worse but not the in-group
accent speaker. The assumption that out-group accent speaker have less linguistic abilities is a
clear indication of region-specific clichés and stereotypes.
The difference between the two regional accents also pertains when controlling for the
guessed rank of the EPs. EPs choose tournament more often when they thought they were
better than their opponent, but this does not change the size or the significance of the
treatment variables.
To control for individual preferences that might affect the choice of the payment scheme, we
elicited social preferences regarding the opponent and furthermore controlled for tournament
aversion (task 6) and risk aversion (task 7). In all cases the results remain stable. EPs who
indicated tournament aversion tend to opt for competition less often while envious people are
more likely to engage in tournament. Moreover, there are no interaction effects between the
accent treatments and gender, indicating that men and women exhibit the same behavior.
Finally, EPs were asked to fill in a questionnaire (task 8) that provides additional information
about their personal biographies and attitudes towards language. These results allowed us to
capture the EPs’ behavior more precisely. Using 36 validated rating scales from [45], we
calculated a measure of linguistic loyalty by aggregating EPs’ attitudes towards the use of
regional language varieties in everyday contexts (e.g., school or family. Further details on the
measure along with the individual items of all rating scales are provided in the Supporting
Information, cf. SI2 and Fig. S1). This measure allowed us to distinguish N = 134 EPs who
show a high loyalty to regional varieties (Table S2; Panel A). The results illustrate the
complementarity of experiments and questionnaires in exploring the link between
economically relevant behavior and stated attitudes. Those EPs who are classified as being
loyal to regional varieties are not equally loyal to all regional accents. On the one hand, they
are loyal to the in-group regional accent. Matched with the Thuringian accent sample, they
avoid tournament significantly more often (rr = .364, p < .05) thus indicating a similarityattraction effect. On the other hand, they choose tournament significantly more often
(rr = 3.453, p < .001) when confronted with the distant Bavarian accent.
15
Fig. 5. Relative risk ratios (rr; log scaled). Pooled refers to the joint results for all tasks using clustered standard
errors at the individual level; the remaining graphs present results per task. Within refers to the Analyses–First
Differences stage in Fig. 1 (within-speaker differences) and Between to the Analyses–Second Difference stage
(differences between speakers). A rr of one (e.g., Within Bav-Stand; Tournament) would indicate an equal
likelihood that EPs choose tournament whether listening to Bavarian accent (Bav) or standard accent (Stand)
while, e.g., a rr of 2.46 would indicate that EPs were 2.46 times more likely to choose tournament when listening
to the Bavarian accent than when the same LI were to speak standard accent; A rr of less than one (e.g., Within
Thur-Stand; Tournament) indicates that EPs avoid tournament when listening to the Thuringian accent (Thur)
more often than in the standard accent treatment (Stand).
Conclusion
Our experimental approach allows us to evaluate accent discrimination in economically
relevant situations. Each of the tasks performed in the experiment addresses different
cognitive capacities. Our experimental setup requires EPs to then compare their own
capacities with the LIs’ expected cognitive capacities. EPs reveal the result of this comparison
through their choice of a payment scheme. If they believe that they can outperform the LI they
choose competition over cooperation.
Varying the accent exogenously, we find that the economic behavior of the interaction
partners is undoubtedly influenced by the use of regional accent or standard accent (first
hypothesis). However, it turns out that only the out-group regional accent affects economic
behavior, indicating that regional accents also transport socio-symbolic information about the
speaker [46]. This is a clear pattern of in-group vs. out-group behavior (second hypothesis)).
Since EPs are more likely to try and outcompete the opponent (i.e. choose competition) when
being matched with the distance accent LI, we interpret this as feeling of cognitive superiority
16
against the out-group speaker (third hypothesis).
Looking at the four tasks separately, we observe effect heterogeneity related to the cognitive
dimensions tested in the experiment. In the language and logic tasks, EPs are more likely to
choose tournament against the out-group accent LI (Bavarian). They think they are better.
When being matched with the in-group accent LI (Thuringian) we do not find this behavior.
Beyond that, we find weak indication that EPs are more likely to cooperate (i.e. choose
revenue sharing) with the in-group accent LI in the math task and we do not find any effect in
the memory task.
One explanation for the effect heterogeneity is that EPs consciously or subconsciously relate
language and combination tasks, but not math and memorization tasks, to the language
treatment. In that case, regional clichés and stereotypes about the out-group accent would
drive the EPs’ expectation about the opponent’s performance in language related tasks.
Another potential explanation may relate to the EPs’ familiarity with the type of task. While
mental arithmetic and memorization are explicitly trained from early on in kindergarten and at
school, cognitive tests (so called brain teasers that are commonly used in assessment centers)
require combinational logic that appears only later in the school curriculum—if at all. To the
extent that (i) everyone received training in math and memorization at school and (ii) almost
everyone has had the experience that sometimes somebody else was better in solving these
tasks, it may be rational to avoid competition. By contrast, language and combinational logic
tasks are not explicitly trained at school thus leaving more room for assumptions about the
opponent’s performance. This is where regional clichés and stereotypes come into play. This
interpretation relates to [47] who find that while trained persons tend to underestimate their
performance, untrained persons tend to overrate their performance and ability. In our context,
this may also explain why experimental participants tend to cooperate with the speaker of
their own regional accent in the math task—thus looking for trustful support—while they
don’t when the same person speaks standard language.
Since our results do not allow us to further explore these potential explanations, we refer them
to future research. Based on our findings, we conclude that regional accents can encourage
clichés and stereotypes that affect individual behavior. More generally, this carries
implications for both, speakers and listeners. From the perspective of the listener, stereotypes
may be goal-oriented [48] as they help reach a decision. But they also may be misleading and
thus not economically effective. This opens up an interesting perspective for the speaker: the
use of regional accents can be strategically employed to persuade or manipulate a
communication partner.
17
Tables
Stage 1
Task
Language Informants (LI)
1
Listening Comprehension
2
Mathematics
X
3
Logic
X
4
Language
X
5
Memory
X
6
Tournament Aversion
7
Risk Aversion
8
Questionnaire
Stage 2
Experimental Participants (EP)
X
X
X
X
X
X
X
X
Table 1. Procedure of the experiment. Tasks 2–5 (bold) are the four experiments that are
performed by LIs in stage 1. Tasks 1–8 are subsequently performed by the EPs in stage 2. In
this set of tasks, EPs can choose their degree of interaction with the LIs.
18
Origin of speaker
Revenue sharing
Tournament
Piece rate
Number of observations
Pearson χ2
Fisher’s exact
Standard Accent
Thuringia
Bavaria
29
41
17.68%
25.62%
35
27
21.34%
16.88%
100
92
60.98%
57.50%
164
160
0.185
0.185
Regional Accent
Thuringia
Bavaria
37
52
25.69%
26.00%
27
62
18.75%
31.00%
80
86
55.56%
43.00%
144
200
0.022
0.021
Table 2. Summary statistics of payment scheme choice pooled over all tasks. Table 2 shows
the number of times EPs chose each payment scheme by accent and LI origin pooled over all
tasks.
19
Constant
(1)
All
RS
Tourn
-1.586**
-2.425***
(0.638)
(0.747)
(2)
Math
RS
Tourn
-2.905**
-3.960**
(1.440)
(1.893)
(3)
Logic
RS
Tourn
-4.405*** -3.315**
(1.549)
(1.643)
(4)
Language
RS
Tourn
-0.709
-1.619
(1.619)
(1.224)
(5)
Memory
RS
Tourn
-1.795
-1.803
(1.196)
(1.434)
0.088
(0.316)
1.122**
(0.541)
1.060
(0.764)
-0.109
(0.662)
-0.263
(0.688)
0.003
(0.673)
-0.512
(0.546)
0.337
(0.602)
0.535
(0.686)
-0.255
(0.306)
1.096**
(0.521)
0.884
(0.711)
-0.161
(0.673)
-0.364
(0.637)
-0.203
(0.644)
-1.826***
(0.618)
0.689
(0.582)
0.853
(0.636)
0.883**
(0.426)
-0.030
(0.306)
0.478
(0.298)
-0.105
(0.316)
0.019
(0.026)
0.824***
(0.212)
-0.805***
(0.215)
656
-1.084
(0.728)
-0.847
(0.995)
0.115
(0.961)
1.748*
(0.896)
0.248
(0.908)
2.258***
(0.815)
0.182
(0.796)
-0.228
(0.879)
0.096*
(0.055)
-0.272
(0.389)
0.271
(0.379)
0.066
(0.070)
0.907*
(0.500)
-1.643***
(0.568)
164
0.110**
(0.054)
-0.059
(0.541)
0.721
(0.536)
0.026
(0.060)
1.263***
(0.434)
-0.973**
(0.440)
164
-0.036
(0.061)
0.110
(0.502)
0.374
(0.481)
0.004
(0.043)
1.144***
(0.399)
-0.301
(0.394)
164
0.036
(0.042)
-0.478
(0.424)
0.340
(0.409)
0.012
(0.051)
0.101
(0.434)
-0.785*
(0.444)
164
Accent:
Thuringian 0.438
(0.304)
Standard
German:
Bavarian
0.453
(0.297)
Bavarian X
Accent
Logic
Language
Memory
Age
Envious
Female
Observations
-0.150
(0.408)
-1.491***
(0.292)
-1.200***
(0.287)
-0.766***
(0.259)
0.049**
(0.022)
-0.205
(0.222)
0.421**
(0.214)
Table 3. Multinomial logit model of scheme choice. To assess the statistical significance of
the observation in Table 2 while controlling for session effects and socio-economic
characteristics, we estimate the multinomial logit model outlined in Equation 1, adding the
variable Envious as control, in order to control for a general tendency to prefer tournaments.
We observe that EPs do not chose the tournament more often when perceiving the Thuringian
accent, but there is a significant increase in tournament take up over all tasks when EPs
perceive the Bavarian accent. Standard errors in parentheses (clustered on the individual level
in model (1)). Multinomial logit model, dependent variable Choice of payment scheme;
*p < .10, **p < .05, ***p < .001
20
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Sapi, Geza and Suleymanova, Irina, Consumer Flexibility, Data Quality and Targeted
Pricing, November 2013.
116
Hinloopen, Jeroen, Müller, Wieland and Normann, Hans-Theo, Output Commitment
Through Product Bundling: Experimental Evidence, November 2013.
Published in: European Economic Review, 65 (2014), pp. 164-180.
115
Baumann, Florian, Denter, Philipp and Friehe Tim, Hide or Show? Endogenous
Observability of Private Precautions Against Crime When Property Value is Private
Information, November 2013.
114
Fan, Ying, Kühn, Kai-Uwe and Lafontaine, Francine, Financial Constraints and Moral
Hazard: The Case of Franchising, November 2013.
113
Aguzzoni, Luca, Argentesi, Elena, Buccirossi, Paolo, Ciari, Lorenzo, Duso, Tomaso,
Tognoni, Massimo and Vitale, Cristiana, They Played the Merger Game:
A Retrospective Analysis in the UK Videogames Market, October 2013.
Published in: Journal of Competition Law and Economics under the title: “A Retrospective
Merger Analysis in the UK Videogame Market”, (10) (2014), pp. 933-958.
112
Myrseth, Kristian Ove R., Riener, Gerhard and Wollbrant, Conny, Tangible
Temptation in the Social Dilemma: Cash, Cooperation, and Self-Control,
October 2013.
111
Hasnas, Irina, Lambertini, Luca and Palestini, Arsen, Open Innovation in a Dynamic
Cournot Duopoly, October 2013.
Published in: Economic Modelling, 36 (2014), pp. 79-87.
110
Baumann, Florian and Friehe, Tim, Competitive Pressure and Corporate Crime,
September 2013.
109
Böckers, Veit, Haucap, Justus and Heimeshoff, Ulrich, Benefits of an Integrated
European Electricity Market, September 2013.
108
Normann, Hans-Theo and Tan, Elaine S., Effects of Different Cartel Policies:
Evidence from the German Power-Cable Industry, September 2013.
Published in: Industrial and Corporate Change, 23 (2014), pp. 1037-1057.
107
Haucap, Justus, Heimeshoff, Ulrich, Klein, Gordon J., Rickert, Dennis and Wey,
Christian, Bargaining Power in Manufacturer-Retailer Relationships, September 2013.
106
Baumann, Florian and Friehe, Tim, Design Standards and Technology Adoption:
Welfare Effects of Increasing Environmental Fines when the Number of Firms is
Endogenous, September 2013.
105
Jeitschko, Thomas D., NYSE Changing Hands: Antitrust and Attempted Acquisitions
of an Erstwhile Monopoly, August 2013.
Published in: Journal of Stock and Forex Trading, 2 (2) (2013), pp. 1-6.
104
Böckers, Veit, Giessing, Leonie and Rösch, Jürgen, The Green Game Changer: An
Empirical Assessment of the Effects of Wind and Solar Power on the Merit Order,
August 2013.
103
Haucap, Justus and Muck, Johannes, What Drives the Relevance and Reputation of
Economics Journals? An Update from a Survey among Economists, August 2013.
Forthcoming in: Scientometrics.
102
Jovanovic, Dragan and Wey, Christian, Passive Partial Ownership, Sneaky
Takeovers, and Merger Control, August 2013.
Published in: Economics Letters, 125 (2014), pp. 32-35.
101
Haucap, Justus, Heimeshoff, Ulrich, Klein, Gordon J., Rickert, Dennis and Wey,
Christian, Inter-Format Competition Among Retailers – The Role of Private Label
Products in Market Delineation, August 2013.
100
Normann, Hans-Theo, Requate, Till and Waichman, Israel, Do Short-Term Laboratory
Experiments Provide Valid Descriptions of Long-Term Economic Interactions? A
Study of Cournot Markets, July 2013.
Published in: Experimental Economics, 17 (2014), pp. 371-390.
99
Dertwinkel-Kalt, Markus, Haucap, Justus and Wey, Christian, Input Price
Discrimination (Bans), Entry and Welfare, June 2013.
98
Aguzzoni, Luca, Argentesi, Elena, Ciari, Lorenzo, Duso, Tomaso and Tognoni,
Massimo, Ex-post Merger Evaluation in the UK Retail Market for Books, June 2013. Forthcoming in: Journal of Industrial Economics.
97
Caprice, Stéphane and von Schlippenbach, Vanessa, One-Stop Shopping as a
Cause of Slotting Fees: A Rent-Shifting Mechanism, May 2012.
Published in: Journal of Economics and Management Strategy, 22 (2013), pp. 468-487.
96
Wenzel, Tobias, Independent Service Operators in ATM Markets, June 2013.
Published in: Scottish Journal of Political Economy, 61 (2014), pp. 26-47.
95
Coublucq, Daniel, Econometric Analysis of Productivity with Measurement Error:
Empirical Application to the US Railroad Industry, June 2013.
94
Coublucq, Daniel, Demand Estimation with Selection Bias: A Dynamic Game
Approach with an Application to the US Railroad Industry, June 2013.
93
Baumann, Florian and Friehe, Tim, Status Concerns as a Motive for Crime?,
April 2013.
92
Jeitschko, Thomas D. and Zhang, Nanyun, Adverse Effects of Patent Pooling on
Product Development and Commercialization, April 2013.
Published in: The B. E. Journal of Theoretical Economics, 14 (1) (2014), Art. No. 2013-0038.
91
Baumann, Florian and Friehe, Tim, Private Protection Against Crime when Property
Value is Private Information, April 2013.
Published in: International Review of Law and Economics, 35 (2013), pp. 73-79.
90
Baumann, Florian and Friehe, Tim, Cheap Talk About the Detection Probability,
April 2013.
Published in: International Game Theory Review, 15 (2013), Art. No. 1350003.
89
Pagel, Beatrice and Wey, Christian, How to Counter Union Power? Equilibrium
Mergers in International Oligopoly, April 2013.
88
Jovanovic, Dragan, Mergers, Managerial Incentives, and Efficiencies, April 2014
(First Version April 2013).
87
Heimeshoff, Ulrich and Klein Gordon J., Bargaining Power and Local Heroes,
March 2013.
86
Bertschek, Irene, Cerquera, Daniel and Klein, Gordon J., More Bits – More Bucks?
Measuring the Impact of Broadband Internet on Firm Performance, February 2013.
Published in: Information Economics and Policy, 25 (2013), pp. 190-203.
85
Rasch, Alexander and Wenzel, Tobias, Piracy in a Two-Sided Software Market,
February 2013.
Published in: Journal of Economic Behavior & Organization, 88 (2013), pp. 78-89.
84
Bataille, Marc and Steinmetz, Alexander, Intermodal Competition on Some Routes in
Transportation Networks: The Case of Inter Urban Buses and Railways,
January 2013.
83
Haucap, Justus and Heimeshoff, Ulrich, Google, Facebook, Amazon, eBay: Is the
Internet Driving Competition or Market Monopolization?, January 2013.
Published in: International Economics and Economic Policy, 11 (2014), pp. 49-61.
Older discussion papers can be found online at:
http://ideas.repec.org/s/zbw/dicedp.html
ISSN 2190-9938 (online)
ISBN 978-3-86304-176-2